Data correction features such as applied to textual data are typically designed to have the same behavior or output for all users based on a particular user input. This behavior is then fixed at the time when the product in which the feature is incorporated ships. For example, spell checkers have existed for some time but with limited capabilities. The checker is typically shipped with a limited dictionary of terms that attempts to check the spelling of words that users will mistype, misspell, etc. It is then left to the user to build up the dictionary with the corrections to terms that the user will typically need checked when editing documents or entering text.
This deficiency applies not only to text entry, but also to linguistics, punctuation, grammar, and different languages for which product features are to be included. The conventional processes attempt to address the needs of a dominant set or broad market of general users, and therefore, do not assist those users who can benefit from more specialized correction techniques.